JP7064080B2 - Photosensitized chemical amplification resist (PS-CAR) model calibration - Google Patents

Description

Cross-reference to related applications This application is a "Photo-sensitized Chemically Amplified Resist (PS-CAR) model" filed on February 19, 2016.
Calibration) ”claims priority under US Patent Application 15 / 048,619, the entire contents of which are incorporated herein by reference.

The present invention relates to a system and method for substrate processing, and more particularly to a method and system for photosensitizing chemical amplification resist (PS-CAR) model calibration.

In lithography patterning of semiconductor devices, the shrinking technology nodes and the associated feature sizes are pushing wavelengths into the extreme ultraviolet (EUV) range. At this time, EUV light sources are still being actively developed and are now developing to the lighting levels of previous generation light sources and cannot bring about this. Resist chemistry and related methods called Photo-Sensitized Chemically-Amplified resist (PS-CAR) to address these shortcomings and utilize current generation EUV light sources. Has been developed. PS-CAR, like conventional chemically amplified resist (CAR), utilizes the acid generated inside the resist feature for deprotection, unlike CAR, which uses only one patterned exposure. The acid is produced in a two-step lighting process.

In PS-CAR, a pattern (latent image in the resist) having a relatively small amount of acid generated is generated, and at the same time, a photosensitizer (photosensitizer) (from a photosensitizer generator added to the PS-CAR resist, for example) is generated. A first pattern exposure is often used at the EUV frequency to produce a photosensitizer) (PS) compound. Both the acid and the photosensitizer (PS) are produced only on the irradiated portion of the PS-CAR resist during the first pattern exposure. After that, flood exposure, that is, exposure without a pattern, is performed with light having a second wavelength different from that of the first patterned exposure. PS-CAR resist chemistry has been selected so that the photosensitizer (PS) is sensitive to the wavelength of the second light used in the second flood exposure, but the other resist components are not. To. The sensitizer (PS) can cause further acid production during flood exposure, which can be accompanied by, for example, a 10-fold increase in acid concentration, as long as it is present in the pattern formed during the first EUV patterned exposure. .. This photosensitizer-induced increase in acid concentration significantly increases contrast, and more process tolerance, especially with respect to the RLS (Resolution-Line Width Roughness-Sensitivity) trade-off. Enables range. Therefore, PS-CAR presents an effective technology for EUV lithography, because it enables the productive use of EUV light sources and lithography at current output levels. be.

It should be noted here that the PS-CAR process may include, for example, an additional step between EUV patterned exposure and flood exposure. The above description has been simplified for clarity. Also, in some PS-CAR chemistry embodiments, no acid may be produced during the first EUV patterned exposure, only a photosensitizer may be produced, and the produced photosensitizer may be flooded. Causes the production of all acids during exposure.
Alternatively, as mentioned above, a small amount of acid can be produced, which is the quenching events (depending on the amount of quencher present in the PS-CAR resist). Can be effectively consumed by competing chemical reactions such as.

The deposition, administration, patterning and development of PS-CAR resist can be a very sensitive process in some embodiments. Due to the complexity of PS-CAR resist chemistry and the scale of patterned features, many variables can contribute to the quality of the resist mask and thus to the resulting etched features. Although resist patterning models have been used to predict resist layer and pattern quality and fine-tune resist processing parameters, any of the conventional models are suitable for patterning PS-CAR for a variety of reasons. not. First, the PS-CAR resist processing flow includes additional steps not required by conventional CAR resist flows. Earlier models did not consider these additional flow steps. Second, PS-CAR resists are more sensitive to EUV and UV exposures than conventional CAR resists, and conventional models do not take such sensitivity into account. Third, conventional models are designed with preset parameters tuned to the chemistry of traditional CAR chemistry rather than PS-CAR chemistry. Those of skill in the art will recognize various additional drawbacks of conventional models used in the simulation of conventional CAR resists.

Methods and systems for PS-CAR photoresist model calibration are described. In embodiments, the method comprises calibrating the initial conditions for simulation of at least one process parameter of a lithography process using radiation sensitive materials. In such an embodiment, the radiation sensitive material has a first light wavelength activation threshold that controls the formation of acids up to the first acid concentration in the radiation sensitive material and controls the production of photosensitizer molecules in the radiation sensitive material. , A second light wavelength activation threshold capable of exciting photosensitizer molecules in a radiation sensitive material that produces an acid having a second acid concentration greater than the first acid concentration, wherein the second light wavelength is the first. It has a second light wavelength activation threshold, which is different from one wavelength. Further, the method comprises performing a lithography process using at least one pre-specified process parameter.

Another embodiment of the method comprises receiving the physical parameters of the radiation sensitive material for use in the lithography process at the input interface. The method may also include receiving exposure parameters at the input interface associated with at least one of a first radiation exposure step and a second radiation exposure step of the lithography process. In addition, the method may include calculating the profile of the radiation sensitive material using a data processor in response to physical and radiation exposure parameters according to a lithography process model. In embodiments, the method may include receiving feedback at the input interface that represents an error value that corresponds to the comparison between the profile of the radiation sensitive material and the experimental verification of the model. In addition, the method may include optimizing at least one of the physical and exposure parameters using a data processor in response to feedback. Further, the method responds to the determination that the error value is within the error threshold margin by producing an output in the output interface that includes at least one of the optimized physical parameters and the optimized exposure parameters. , May include steps to generate.

The accompanying drawings, which are incorporated herein and constitute a portion of the present specification, show embodiments of the invention, and together with a schematic description of the invention given above and a detailed description below, the present invention. It serves to explain the invention.
It is a figure which shows the embodiment of the semiconductor wafer processing system. It is a figure which shows the embodiment of the photosensitizer and the acid concentration profile after the EUV pattern exposure step in a PS-CAR patterning process. It is a figure which shows the cross section of the device after the EUV patterning exposure step in a PS-CAR patterning process. It is a figure which shows the embodiment of the photosensitizer and the acid concentration profile after a flood exposure step in a PS-CAR patterning process. It is a figure which shows the cross section of the device after a flood exposure step in a PS-CAR patterning process. FIG. 5 shows a photosensitizer and acid concentration profile prior to a flood exposure step that has the illustrated effect of unmitigated EUV shot noise in the PS-CAR patterning process. FIG. 5 shows a photosensitizer and acid concentration profile after a flood exposure step with the illustrated effect of unmitigated EUV shot noise in the PS-CAR patterning process. It is a figure which shows the photosensitizer concentration profile before the EUV shot noise mitigation step and the acid concentration profile after the EUV shot noise mitigation step in the PS-CAR patterning process according to the embodiment of this invention. FIG. 5 shows an experimental acid concentration profile after the EUV shot noise mitigation step and after the flood exposure step in the PS-CAR patterning process according to an embodiment of the present invention. It is a flowchart which shows the process flow between PS-CAR patterning process by embodiment of this invention. It is a schematic block diagram which shows one Embodiment of the data processing system configured for PS-CAR photoresist simulation. It is a schematic block diagram which shows one Embodiment of the system for PS-CAR photoresist simulation. It is a schematic flowchart which shows one Embodiment of the method of calibrating the input parameter of a PS-CAR photoresist model. It is a schematic flowchart which shows one Embodiment of the method of calibrating the input parameter of a PS-CAR photoresist model. It is a schematic flowchart which shows one Embodiment of the method for simulating a PS-CAR photoresist. It is a schematic flowchart which shows one Embodiment of the method for simulating a PS-CAR photoresist. It is a schematic input / output diagram which shows the embodiment of the input / output data set for a PS-CAR photoresist model. FIG. 3 is a schematic parameter design diagram showing an embodiment of an input dataset for a PS-CAR photoresist model. FIG. 3 is a schematic parameter design diagram showing an embodiment of an output data set for a PS-CAR photoresist model. It is a schematic parameter design diagram which shows the operation of one Embodiment of the EUV optical module of a PS-CAR photoresist model. It is a schematic parameter design diagram which shows the operation of one Embodiment of the EUV exposure module of a PS-CAR photoresist model. It is a schematic parameter design diagram which shows the operation of one Embodiment of the pre-PEB module of a PS-CAR photoresist model. It is a schematic parameter design diagram which shows the operation of one Embodiment of the UV optical simulator of a PS-CAR photoresist model. It is a schematic parameter design diagram which shows the operation of one Embodiment of the UV flood exposure module of a PS-CAR photoresist model. It is a schematic parameter design diagram which shows the operation of one Embodiment of the PEB module of a PS-CAR photoresist model. It is a schematic parameter design diagram which shows the operation of one Embodiment of the development module of a PS-CAR photoresist model. It is a schematic parameter design diagram which shows the operation of one Embodiment of the metrology module of a PS-CAR photoresist model.

Embodiments of the present invention relate to the design and control of processes, devices and systems for patterning layers on a substrate in semiconductor manufacturing.

In the following description, masks, coaters / developers, exposure tools and specific geometries of various components and processes are used to facilitate a complete understanding of the invention and for purposes of illustration and not limitation. Specific details such as the geometry are described. However, it should be understood that the invention can be practiced in other embodiments that deviate from these specific details.

In the following description, the terms radiation sensitive material and photoresist can be used interchangeably, and photoresist is only one of many suitable radiation sensitive materials for use in photolithography. Similarly, in the following, the term substrate representing a workpiece being processed can be used interchangeably with terms such as semiconductor wafers, LCD panels, light emitting diodes (LEDs), photovoltaic cell (PV) device panels, etc. All of these processes are within the scope of the claims.

Throughout the specification, "one embodiment" or "embodiment" means that the particular features, structures, materials or properties described in connection with an embodiment are included in at least one embodiment of the invention. It means, but it is not intended to be present in every embodiment. Therefore, throughout the specification, the appearance of the expression "in one embodiment" or "in an embodiment" in various places does not necessarily refer to the same embodiment of the invention. Moreover, a plurality of specific features, structures, materials or properties can be combined in any suitable manner in one or more embodiments.

The various movements are described as multiple individual movements in the manner most useful to the understanding of the present invention. However, the order of description should not be construed to mean that these actions are necessarily order dependent. In particular, these operations need not be performed in the order presented. The described operations may be performed in a different order than the described embodiments. Various additional actions may be performed and / or the described actions may be omitted in the additional embodiments.

Furthermore, the photosensitized chemical amplification resist (PS-CAR) is not limited to the resist (photoresist), but similar light-sensitive chemistries are anti-reflection coating (ARC), lower anti-reflection. It can be carried out by coating (BARC), developer dissolving lower anti-reflection coating (DBARC), overcoat material, smart slim material and the like. The PS-CAR chemistry and methods described herein are applicable to all of these materials and their patterning, so the terms resist, photoresist and radiation sensitive materials are hereinafter all of these materials. Used interchangeably to point to.

The concept of a photosensitized chemical amplification resist (PS-CAR) is described in some detail below. In contrast to traditional resist treatment, where a single patterned exposure (ie, via a mask) produces a deprotected (positive tone) or protected (negative tone) resist region that defines the soluble and insoluble regions, respectively. The PS-CAR process relies on a first patterned exposure at the first wavelength of light to amplify the sensitivity of the resist to the second chemically selective flood exposure at the second wavelength of light that defines the final pattern. The second light wavelength is selected to be different from the first light wavelength of light. This allows for higher sensitivity patterning when the photon density is low. The photosensitizer (PS) is produced only in the exposed area of the resist during the first EUV patterned exposure. An electron beam (eBeam), KrF or ArF exposure can also be used for the first patterned exposure.

The choice of flood exposure wavelength is dictated by the requirement to maximize absorption by the photosensitizer (PS) while minimizing absorption by the photoacid generator (PAG) or PS generator in the resist. To. Typically, the light wavelength of the flood exposure is in the UV portion of the light spectrum. The photosensitizer (PS) excited by the second flood exposure is capable of decomposing photoacid generator (PAG) molecules in its vicinity and produces acid in the region exposed by the first EUV patterned exposure. It can be kept free of acid formation in essentially unexposed areas while causing amplification. This means that there is no DC bias shift typically present in conventional flood exposure processes.

Thus, the resist can include a separate activation threshold that allows the formation of chemicals in the resist to occur at different times under different process conditions before being developed. Specifically, the concept is to isolate the formation of photosensitizer (PS) and acid amplification from each other within the resist. In some PS-CAR chemistry embodiments, only the photosensitizer is produced during the first EUV patterned exposure, no acid is produced, and acid production and amplification is complete during the subsequent second flood exposure. Occurs in. In these embodiments, there is no overlap in the light sensitivity ranges of the photosensitizer generator and the photoacid generator (PAG). In other PS-CAR chemistry embodiments, at the same time as a relatively small amount of acid, typically less than about half of the final amount of acid produced after amplification, during the first EUV patterned exposure. The photosensitizer generator and photoacid generator (PAG) photosensitivity ranges can slightly overlap so that the photosensitizer (PS) is produced. The amount of this initially produced acid is then amplified in the second flood exposure. In an exemplary embodiment of PS-CAR, the first (EUV) light wavelength can be less than 300 nm and the second light wavelength used for the second flood exposure can be greater than 300 nm, typically about 365 nm. ..

In embodiments, as described above, the resist comprises a photosensitizer generator having a first light wavelength activation threshold that controls the formation of photosensitizer (PS) molecules in the resist layer and a photosensitizer generator in the resist layer. A photoacid-producing (PAG) compound having a second light wavelength activation threshold that controls acid production and amplification can be included, the second activation wavelength being different from the first activation wavelength. Photosensitizer molecules can be selected to absorb light energy and transfer light energy to other molecules, such as photoacid generators. Photosensitizer (PS) molecules can transfer ground state energy and other molecules can transfer excited state energy. In embodiments, the photosensitizer generator of the PS-CAR resist can include at least one of acetophenone, triphenylene, benzophenone, fluorenone, anthraquinone, phenanthrene or an inducer thereof. In embodiments, the photoacid generator (PAG) may be a cationic photopolymerization initiator capable of converting absorbed light energy into chemical energy, such as an acidic reaction. Photoacid generators (PAGs) include triphenylsulfonium triflate, triphenylsulfonium nonaflate, triphenylsulfonium perfluorooctylsulfonate, triarylsulfonium triflate, and tria. Triarylsulfonium nonaflate, triarylsulfonium perfluorooctylsulfonate, a triphenylsulfonium salt, triarylsulfonium salt (a)
triarylsulfonium salt), triarylsulfonium hexafluoroantimonate salt (a)
triarylsulfonium hexafluoroantimonate salt), N-hydroxynaphthalimide triflate, 1,1-bis [p-chlorophenyl] -2,2,2-trichloroethane (DDT) (1,1-bis [p-chlorophenyl] -2,2,2-trichloroethane (DDT)), 1,1-bis [p-methoxyphenyl] -2,2,2-trichloroethane (1,1-bis [p-methoxyphenyl] -2,2,2- trichloroethane), 1,2,5,6,9,10-hexabromocyclododecane (1,2,5,6,9,10-hexabromocyclododecane), 1,10-dibromodecane (1,10-dibromodecane), 1 , 1-bis [p-chlorophenyl] 2,2-dichloroethane (1,1-bis [p-chlorophenyl] 2,2-dichloroethane), 4,4-dichloro-2- (trichloromethyl) benzhydrol (4, 4-dichloro-2- (trichloromethyl) benzhydrol), 1,1-bis (chlorophenyl) 2-2,2-trichloroethanol (1,1-bis (chlorophenyl) 2-2,2-trichloroethanol), hexachlorodimethylsulfone (1,1-bis (chlorophenyl) 2-2,2-trichloroethanol) Hexochlorodimethylsulfone), 2-chloro-6- (trichloromethyl) pyridine (2-chloro-6- (trichloromethyl) pyridine) or at least one of their inducers can be included.

FIG. 1 is an embodiment of a semiconductor wafer processing system 100. In embodiments, the semiconductor substrate 102, such as a silicon wafer, is inserted into the PS-CAR photoresist coating unit 104. The semiconductor substrate 102 can then be coated with one or more layers of PS-CAR photoresist. The substrate 102 can be delivered to a pattern exposure unit 106, such as an EUV exposure unit, for patterning the PS-CAR photoresist layer. After patterning, the substrate 102 is exposed to a second light wavelength, such as a UV light flood, within the flood exposure unit 108 for further exposure of the PS-CAR photosensitizer and other acid-producing elements of PS-CAR. be able to. The substrate 102 can be delivered to a pattern etching unit 110 for patterned etching of one or more layers on the substrate, as defined by a PS-CAR photoresist patterning mask. The resulting substrate 102 can include one or more physical features 112 formed therein or deposited within one or more layers deposited on the substrate 102. One of skill in the art will recognize that additional steps and / or functional units can be included in the system 100. For example, the wafer 102 may be post exposure bake (PEB) or pre-PEB diffusion (pre-PEB).
diffusion) Can be placed in close proximity to the heating element for the process. In addition, one or more portions of the PS-CAR photoresist layer can be removed prior to etching in a wet etching chamber, cleaning chamber or photoresist selective dry etching chamber. Further, the (s) PS-CAR layer can be developed in a dedicated developing unit or the like. These additional modules or units are not shown to simplify the discussion of the techniques presented herein. These additional details are known to those of skill in the art.

To further aid understanding, FIGS. 2A-2D illustrate the PS-CAR patterning process prior to subsequent development and etching steps. In FIG. 2B, a substrate 250 coated or modified to form an underlayer 260 to be patterned is provided. The PS-CAR resist 270 is applied to the exposed surface of the underlying layer 260 using, for example, a spin-on administration technique. In the first EUV patterned exposure 201, the first light wavelength 290 is exposed onto the PS-CAR resist 270 via the mask 280 in order to form alternating exposed and non-exposed areas inside the PS-CAR resist 270. .. During this exposure, a photosensitizer (PS) is produced from the photosensitizer generator within the exposed area of the PS-CAR resist 270, forming a photosensitizer (PS) concentration profile 220, which are shown in FIG. In 2A, it is shown magnified in Graph 200 with a photosensitizer (PS) 220 and an acid concentration 210, respectively. Depending on the PS-CAR resist chemistry, in some embodiments, inside the PS-CAR resist 270 during the first EUV patterned exposure 101 to form the acid concentration profile 210. Acids are formed from photoacid-producing agent (PAG) molecules. In another embodiment, if there is no overlap between the photosensitivity range of the photosensitizer generator and the photoacid generator (PGA), the acid will be produced during the first EUV patterned exposure 201, as described above. Not done.

After that, as shown in FIG. 2D, the substrate 250 having the base layer 260 and the patterned exposure PS-CAR resist 270 is currently exposed to the second flood 201 using a second light wavelength 290 different from the first light wavelength 290. The second flood exposure receives the photosensitizer (PS) molecules generated in the previously exposed (ie unmasked) region and the acid from the photoacid generator (PAG) molecules in the vicinity thereof. The production is amplified, thereby forming the acid concentration profile 210. The acid concentration profile 210 has a higher peak and therefore has a better contrast than the density profile 210 after the first EUV patterned exposure. Even if the second flood exposure 201 is included, unlike a typical flood exposure process, there is no acid formation in the unexposed (masked) region during the first EUV patterned exposure 201, thus DC. There is no bias and high contrast is maintained. This is because in PS-CAR acid production and amplification occur only in the presence of a photosensitizer (PS). Typically, the photosensitizer (PS) concentration profile 220 undergoes a slight change from the initial photosensitizer (PS) concentration profile 220 after the second flood exposure 201, but in certain chemical embodiments, the light Greater changes can occur between the sensitizer (PS) concentrations 220 and 210. FIG. 2C shows graphs 200 of each of the photosensitizer (PS) profile 220 and the acid concentration profile 210 after the second flood exposure 201.

The substrate with the amplified acid concentration profile 210 currently present in the PS-CAR resist 270, which forms the latent image, is now ready for subsequent patterning process steps. Subsequent patterning process steps include, for example, steps such as firing, developing, and etching of the underlying layer 260 to complete the patterning process after the conventional steps. In some embodiments, additional processing steps, such as a firing step, can be performed between the first EUV patterned exposure 201 and the second flood exposure 201. Further, the process is described herein with PS-CAR resist 270 as an example, but the same process is like a layer comprising PC-CAR components such as ARC, BARC, DBARC, overcoat material and the like. It is applicable to any other material.

2A-2D show what an ideal photosensitizer (PS) and acid concentration profile might look like. FIG. 3A shows exemplary photosensitizer (PS) concentration profile 320 and acid concentration profile 310 with the effect of EUV shot noise obtained during the first EUV patterned exposure 201. EUV shot noise causes deviations from the ideal density profiles 210 and 220, respectively, in FIG. 2A. As shown in FIG. 3B, when such non-ideal photosensitizer (PS) concentration profile 320 and acid concentration profile 310 undergo a second flood exposure 201, the second flood exposure 201 is irregular in the acid concentration profile 310. The sex can be amplified to the final acid concentration profile 315 with reduced contrast. The contrast reduction in the acid concentration profile 315 mainly contributes to the line width roughness (LWR) of the patterning (LER or CER depending on the device type), and measures for reducing this contrast reduction due to EUV shot noise. Is needed to maintain the integrity of the pattern.

We have devised many possible ways to mitigate this contrast loss due to EUV shot noise. Most of these methods are based on including an intermediate step between the first EUV patterned exposure 201 and the second flood exposure 201, where the irregularities resulting from EUV shot noise are smoothed out. , The generated photosensitizer (PS) can be diffused in its vicinity.

FIG. 3C shows graphs of the photosensitizer (PS) concentration profile 320 before the photosensitizer diffusion step and the photosensitizer (PS) concentration profile 325 after the photosensitizer diffusion step. The photosensitizer (PS) concentration profile 325 is smoother than the photosensitizer (PS) concentration profile 320 affected by EUV shot noise and should significantly reduce deviations from the ideal final acid concentration profile. Is. The acid concentration profile 335 after diffusion of the photosensitizer (PS) is also shown in FIG. 3C. With the diffused and smoothed photosensitizer (PS) concentration profile 325, the process proceeds to a second flood exposure to generate and amplify the acid. As shown in FIG. 3D, during this process the final acid concentration profile 340 is achieved and improved beyond the concentration profile 315 of FIG. 3B obtained without steps to reduce EUV shot noise.

Next, with reference to FIG. 4, a flowchart 400 of the PS-CAR patterning process with EUV shot noise mitigation is shown. In step 402, a substrate such as a substrate 250 having a base layer 260 to be patterned formed on the substrate and a PS-CAR resist 170 on the base layer 260 is provided. In step 404, the PS-CAR resist undergoes a first EUV patterned exposure, typically with a first light wavelength within the EUV range, and thus the photosensitizer generator within the PS-CAR resist 270. Activates a first activation threshold for producing a photosensitizer (PS) from. In step 406, the generated photosensitizer (PS) molecules can be diffused to mitigate the effects of EUV shot noise. In step 408, as described above, in order to generate a final acid concentration profile that corrects for the effects of EUV shot noise, the PS-CAR resist 270 is second at a second light wavelength different from the first light wavelength. Upon flood exposure, the second activation threshold is activated to generate and amplify an acid from the photosensitive generator (PAG) molecules in the PS-CAR resist 270.

With reference to FIG. 4, further patterning steps can include conventional patterning steps. For example, a subsequent firing process 410 or the like in which the substrate is heated in the meantime, followed by development in which the PS-CAR resist 270 is developed to form a patterned mask for subsequent processing of the underlying layer 260. Process 412 continues. Finally, the process ends in the actual process 414, where the underlying layer 260 is etched, implanted or modified with a PS-CAR resist developed as a mask. All these processes are well known to those skilled in the art of semiconductor lithography patterning and will not be described in detail here.

In the simplest embodiment, allowing sufficient time between the first EUV patterned exposure and the second flood exposure to generate the photosensitizer (PS) molecules to be diffused is photosensitized. Represents the simplest embodiment of step 406 of diffusing an agent (PS) molecule. However, this method can cause a processing throughput penalty by retaining the substrate due to diffusion during exposure.

FIG. 5 is a schematic block diagram showing an embodiment of a data processing system configured for PS-CAR photoresist simulation. In one embodiment, the elements shown in FIG. 6 can be implemented in a computer system similar to the computer system 500 described in FIG. In various embodiments, the computer system 500 can be a server, mainframe computer system, workstation, network computer, desktop computer, laptop, and the like. The present embodiment is not specific to any particular computing platform or any particular computer configuration, but is associated with sufficient computation and processing power of the system and simulations performed as described herein. Those skilled in the art will recognize that it should include sufficient memory to accommodate many parallel computations.

For example, as illustrated, the computer system 500 includes one or more processors 502A-502N connected to system memory 504 via bus 506. The computer system 500 is connected to a (s) input / output (I / O) controllers 510 and a bus 506 connected to devices such as a cursor control device 512, a keyboard 514, and (s) displays 516. The network interface 508 and the like are further included. In some embodiments, a given entity (eg, the PS-CAR simulation tool shown in FIG. 6) can be implemented using a single instance of computer system 500, but in other embodiments. In embodiments, the plurality of nodes forming the plurality of such systems or computer systems 500 are configured to host different parts or examples of embodiments (eg, calibration unit 602 and PS-CAR simulation tool 604). Can be done.

In various embodiments, the computer system 500 can be a single processor system including one processor 502A, or a multi containing two or more (eg, 2, 4, 8 or other suitable number) processors. It can also be a processor system. The (s) processors 502A to 502N can be any processor capable of executing program instructions and performing quantitatively intensive calculations. For example, in various embodiments, the (s) processors 502A-502N are, for example, x86, POWERPC®, ARM®, SPARC® or MIPS® ISAs, etc. , Various arbitrary instruction set architectures (ISAs), or other general purpose processors or embedded processors that implement any suitable ISA. In a multiprocessor system, each of the processors 502A to 502N can implement the same ISA, but is not required. Also, in some embodiments, the at least one processor 502A-502N can be a graphics processing unit (GPU) or other dedicated graphics rendering device.

The system memory 504 can be configured to store program instructions and / or data accessible by the processors 502A-502N. For example, memory 504 can store the software program and / or database shown in FIGS. 7-10. In various embodiments, the system memory 504 is any suitable suitable, such as static random access memory (SRAM), synchronous dynamic RAM (SDRAM), non-volatile / flash type memory, or any other type of memory. It can be implemented using memory technology. As shown, for example, as described above, program instructions and data that perform a particular operation can be stored in system memory 504 as program instructions 518 and data storage 520, respectively. In other embodiments, program instructions and / or data may be received, transmitted or stored by or on a different type of computer accessible medium separate from system memory 504 or computer system 500. can. Generally, the computer-accessible medium is any tangible fixed storage or memory medium such as an electrical, magnetic or optical medium, such as a disk or CD / CD connected to the computer system 500 via bus 506. It can include a DVD-ROM or a non-volatile memory (eg, such as a "flash" memory).

In embodiments, the bus 506 is of a processor 502, a system memory 504, and any peripheral device connected via the (s) I / O controllers 510, including a network interface 508 or other peripheral interface. It can be configured to coordinate I / O communication in between. In some embodiments, the bus 506 is arbitrary to convert the data signal from one component (eg, system memory 504) into a format suitable for use by another component (eg, processors 502A to 502N). It can perform the required protocol, timing or data conversion. In some embodiments, the bus 506 is for devices mounted via various types of peripheral buses, for example variations of the Peripheral Component Interconnect (PCI) bus standard or the Universal Serial Bus (USB) standard. Can include support. In some embodiments, the operation of the bus 506 may be split into two or more separate components, such as, for example, a north bridge and a south bridge. Further, in some embodiments, some or all operations of the bus 506, such as an interface to system memory 504, can be incorporated directly into the (s) processors 502A-502N.

The network interface 508 is configured to allow the exchange of data between the computer system 500 and other devices such as other computer systems attached to the PS-CAR simulation tool as shown in FIG. Can be done. In various embodiments, the network interface 508 is telecommunications, such as an analog voice network or a digital fiber communication network, over a common wired or wireless data network, such as an appropriate type of Ethernet network. It can support communication over telecommunications networks, over storage area networks such as fiber channel SANs, or over the appropriate type of network and / or protocol.

The I / O controller 510 may, in some embodiments, be one or more display terminals, keyboards, keypads, touch screens, scanning devices, voice or optical recognition devices, or one or more computer systems. Allows the 500 to connect to any other device for inputting or reading data. The plurality of input / output devices can be in the computer system 500 or can be distributed on various nodes of the computer system 500. In some embodiments, similar I / O devices can be isolated from the computer system 500 and can interact with the computer system 500 via a wired or wireless connection, for example on network 508.

As used herein, the terms "tangible" and "non-transitory" are intended to describe computer-readable storage media (or "memory"), except for the propagation of electromagnetic signals. However, it is not intended to limit the types of physical computer readable storage devices contained within the term computer readable medium or memory. For example, the term "non-temporary computer readable medium" or "tangible memory" is intended to include types of storage devices that do not necessarily store information permanently, such as RAM. Program instructions and data stored in non-temporary form on tangible computer-accessible storage media are then delivered by transmission media or via communication media such as networks and / or wireless links, electrical. It can be transmitted by a signal such as an electromagnetic or digital signal.

As shown in FIG. 5, the memory 504 is a data storage 520 containing program instructions 518 configured to implement the particular embodiments described herein and various data accessible by program instructions 518. And can be included. In embodiments, program instruction 518 can include software elements of the embodiment illustrated in FIG. For example, program instruction 518 can be implemented in various embodiments using any desired programming language, scripting language or programming language and / or combination of programming languages. The data storage 520 contains data that can be used in those embodiments, such as, for example, input parameters, intermediate stream calculated values or output parameters, as illustrated in FIGS. 11-20. In other embodiments, other or different software elements and data may be included.

Those skilled in the art will appreciate that the computer system 500 is merely exemplary and does not limit the scope of the disclosures described herein. In particular, computer systems and devices can include any combination of hardware or software capable of performing the indicated operation. Further, the actions performed by the illustrated components may, in some embodiments, be performed by fewer components or may be distributed across additional components. Similarly, in other embodiments, some actions of the illustrated components may not be performed and / or other additional actions may be available. Accordingly, the systems and methods described herein can be implemented or implemented by other computer system configurations.

FIG. 6 is a schematic block diagram showing an embodiment of the system 600 for PS-CAR photoresist simulation. In one embodiment, the system 600 includes a calibration unit 602 and a PS-CAR simulation tool 604. The calibration device 602 can generate one or more input parameters specific to the PS-CAR chemistry modeled by the PS-CAR simulation tool 604. In one embodiment, the calibration unit 602 may be configured to perform operations associated with one or more embodiments of the methods described in FIGS. 7-8.

The PS-CAR simulation tool 604 includes input parameters generated by the calibration unit, other input parameters specific to the PS-CAR photoresist to be used, system and processing parameters, and specific features to be patterned. Can be received. In response to the input received, the PS-CAR simulation tool 604 can calculate, for example, a numerical model representing the PS-CAR processing method used by the system 100 shown in FIG. In general, the PS-CAR simulation tool 604 can be configured to perform the operations shown in FIGS. 9-10. As mentioned above, the calibration unit 602 and the various modules or units of the PS-CAR simulation tool can be software-defined modules, which are stored in a memory device, eg, as shown in FIG. It is configured to be executed by one or more processing devices.

In embodiments, the input interface 606 can be configured to receive input parameters and other controls and instructions for generating inputs optimized for the PS-CAR simulation tool 604. .. Examples of inputs can include optical parameters of the photoresist, such as refractive index, Dill A and Dill B parameters, and the like. Additional input parameters can include acid production and calcination parameters such as Dell C, quencher feed, amplification parameters, acid / base quench parameters, and acid / base diffusion parameters. Further, development parameters can be received, including, for example, development rate (Rmax / Rmin) parameters and the like. Those skilled in the art will recognize that the input can be an initial condition for these and other parameters. Alternatively, the input received by the input interface 606 can include feedback from physical measurements of verification experiments and the like.

In embodiments, the photoresist profile processor 608 can calculate estimates of the physical characteristics of the photoresist layer in response to received inputs. For example, the photoresist profile processor can calculate models such as photoresist layer thickness, edge sharpness, pattern features such as shot noise, and thickness loss. In addition, the photoresist profile processor 608 contains acid generators, quenchers (photodegradable quenchers or more traditional non-photoresolvable quenchers), precursors (photosensitizer generators) within the photoresist volume. , And the number of light sensitizers (a number) can be specified.

The photoresist profile processor 608 can be further configured to perform one or more of the following operations: a number of precursors for converting precursors to photosensitizers. To identify the acid-induced deprotection reaction of the secondary intermediate UV flood absorbed by the photoresist volume, or to identify the number of photons of the primary exposure, by the primary exposure, or by the secondary intermediate. Identifying the number of acid-producing agents that are converted to acid by photosensitizer activation by UV exposure wavelength or wavelength range and by subsequent acid-producing agent decomposition by excited photosensitizer, by primary exposure, or by primary exposure. Identifying the number of photodegradable quenchers (if applicable) that are decomposed by the secondary intermediate UV exposure wavelength or wavelength range, identifying the large number of acids in the photoresist volume and the quencher neutralization reaction, Determining the number of acid-induced deprotection reactions of the protective polymer, calculating the development of the photoresist volume, and creating a two-dimensional (or three-dimensional) image of the photoresist profile formed by the development of the photoresist volume on the processor. And to identify the dimensional characteristics of the photoresist profile. Those of skill in the art will recognize that these are merely selections of calculations that can be performed by the photoresist profile processor 608.

In embodiments, the parameters calculated by the photoresist profile processor 608 can be provided to the PS-CAR simulation tool 604 via the output interface 612. In another embodiment, the output interface 612 can provide a read or printout of the calculated parameters for experimental verification. In response, engineers or scientists are asked to perform the actual lithography process in PS-CAR chemistry selected according to processing parameters including exposure wavelength and dosing time, photoresist deposition rate, wafer rotation rate, PEB specifications, etc. By executing, the calculated parameters can be verified experimentally. The actual dimensions of the experimentally developed wafer are then physically measured and compared to the model results. The difference between the modeled result and the actual result is provided to the input interface 606 as feedback to the optimization engine 610.

The optimization engine 610 can use one or more optimization algorithms to reduce or eliminate the error between the modeled result and the actual experimental result, and the optimization algorithm is a gradient. Approach algorithms, simplex algorithms, semi-probabilistically simulated annealing algorithms, generic algorithms, or anything else for changing input parameters. In general, error feedback is assigned a number with a directional code to pull or push the input parameters towards a value that produces an overall minimum of error between the model and the actual result.

In some embodiments, the optimization engine 610 is capable of optimizing PS-CAR optical parameters as described above. In addition, the optimization engine 610 can optimize acid production and calcination parameters. Further in a further embodiment, the optimization engine 610 can optimize development parameters. In some embodiments, these three categories of parameters can be optimized independently and in series. Alternatively, multiple categories can be optimized independently and in parallel. Alternatively, multiple categories can be optimized subordinately and serially, or subordinately in parallel. Examples of these optimization techniques are illustrated in FIG.

Once the difference between the actual photoresist feature and the modeled feature reaches the threshold, the optimization engine 610 can terminate the optimization process and the optimized parameters are routed through the output interface 612. It can be provided in the PS-CAR simulation tool 604. Those skilled in the art will recognize that the input interface 606 and the output interface 612 may be hardware-based input / output interfaces. Alternatively, the input interface 606 and the output interface 612 may be software-defined, and the inputs and outputs can be passed between functions or modules of the software as function call parameters or function return values.

In addition to the calibrated parameters provided by the calibration unit 602, the PS-CAR simulation tool 604 can receive one or more process-specific parameters for the actual process to be modeled. The PS-CAR simulation tool 604 can include multiple modules or units, each unit configured to perform some of the process steps and associated model calculations. The units include a primary exposure patterning optical unit 614, a primary exposure patterning unit 616, a pre-PEB unit 618, a secondary exposure patterning unit 620, a secondary exposure unit 622, a PEB unit 624, a developing unit 626 and a metrology unit 628. Can include. The module can run a continuum model. Alternatively, the module can partially execute a probabilistic model. One of ordinary skill in the art will recognize another embodiment.

In embodiments, the primary exposure patterning optical unit 614 can include a simulated EUV source. The simulator can simulate a commercially available optical source used to pattern a PS-CAR photoresist layer. Additional parameters can include intensity, focal length, etc. Further details of the primary exposure patterning optical unit 614 are illustrated in FIG.

In embodiments, the EUV unit 616 is configured to model the response within the PS-CAR photoresist layer in response to EUV exposure from a simulated EUV source. Modeled parameters can include one or more of the following: exposure time / dose, mask feature size, stepper / scanner settings, focus, polarization, etc. Further details of the primary exposure patterning unit 616 are illustrated in FIG.

In embodiments, the pre-PEB unit 618 can model the results of the pre-PEB photosensitizer diffusion process. The pre-PEB unit 618 can be optional in some embodiments, or can be employed at least selectively in response to the pre-PEB diffusion period. Further details of the pre-PEB unit 618 are illustrated in FIG.

In embodiments, the secondary optical unit 620 can be configured to simulate a commercially available UV source. The secondary optical unit 620 can model wavelength, intensity, illumination method, and the like. The secondary optical unit 620 can be used by the UV flood unit 622 to model the physical results of the UV flood process on the PS-CAR photoresist layer. Further details of the secondary optical unit 620 and the UV flood unit 622 are illustrated in FIGS. 17-18, respectively.

In embodiments, the PEB unit 624 can model the reaction of the photoresist to the post-exposure firing process. Modeled parameters can include calcination temperature, calcination time, calcination humidity, etc., further details of the PEB unit 624 are illustrated in FIG.

In embodiments, the developing unit 626 can be configured to model the reaction of the PS-CAR photoresist to the developing process. Modeled parameters can include relative surface rate, inhibition depth and other development conditions. Further details of the parameters modeled by the developing unit 626 are illustrated in FIG.

In embodiments, the Metrogee unit 628 is configured to provide simulated measurements of modeled features on the PS-CAR photoresist layer. The measured values can include resist loss, deprotection level and profile and the like. In some embodiments, continuum model output can be provided. In another embodiment, a probabilistic model output can be provided. Further details of the parameters modeled by the Metrozy unit 628 are illustrated in FIG.

FIG. 7 is a schematic flowchart showing an embodiment of the method 700 for calibrating the input parameters of the PS-CAR photoresist model. In embodiments, the method 700 can include the step of receiving one or more PS-CAR photoresist parameters in block 702. The exposure parameters can be received in blocks 704. At block 706, the method 700 can include the step of calculating the PS-CAR photoresist profile in response to the received PS-CAR photoresist parameters and the received exposure parameters. At block 708, method 700 can include receiving feedback from experimental validation of the PS-CAR photoresist profile. If it is identified in block 710 that the error is within the threshold margin, then the optimized parameters in block 716 are provided as input to the PS-CAR simulation tool. If not, the PS-CAR photoresist parameters and exposure parameters can be optionally optimized in blocks 712 and 714, respectively. The optimization loop can continue until the threshold is met in block 710.

The flowchart illustrated in FIGS. 7-10 illustrates a method of calculating a PS-CAR photoresist profile. FIGS. 7-8 show how to calibrate the model parameters, and FIGS. 9-10 show how to calculate the PS-CAR photoresist profile according to the PS-CAR photoresist model.

FIG. 8 is a schematic flowchart showing an embodiment of the method 800 for calibrating the input parameters of the PS-CAR photoresist model. In an embodiment, method 800 comprises receiving a PS-CAR parameter in block 802. Optical parameters can be optimized in block 804 in response to feedback from experimental validation until the threshold is reached in block 806. Acid production and calcination parameters can be optimized in block 808 in response to feedback from experimental results until the threshold is reached in block 810. In addition, development parameters can be optimized in block 812 in response to feedback from experimental validation until the threshold is reached in block 814. Once the parameters are optimized, they can be provided as input to the PS-CAR simulation tool in block 816.

FIG. 9 is a schematic flowchart showing an embodiment of Method 900 for modeling a PS-CAR photoresist. In an embodiment, the method 900 includes a step of receiving a PS-CAR photoresist parameter input in block 902 and a step of receiving a PS-CAR exposure parameter in block 904. Method 900 further comprises calculating the PS-CAR photoresist profile in block 906 according to the PS-CAR photoresist profile model. At block 908, method 900 comprises generating a PS-CAR photoresist profile output in response to the profile.

FIG. 10 is a schematic flowchart showing an embodiment of a method for modeling a PS-CAR photoresist. In an embodiment, the method 1000 includes a step of receiving a PS-CAR photoresist parameter input in block 1002 and a step of receiving a PS-CAR exposure parameter input in block 1004. At block 1006, the method can include calculating the response to EUV exposure. In block 1008, the method 1000 can include a step of calculating the response to the pre-PEB diffusion step. At block 1010, the method can include the step of calculating the response to the UV flood. At block 1012, method 1000 can include the step of calculating the response to PEB. Block 1014 can include a step of calculating a development model. Block 1016 includes a step of calculating the Metrogee result. Block 1018 includes a step that provides an output in response to the values calculated in steps 1006-1016.

FIG. 11 is a schematic input / output diagram showing an embodiment of an input / output dataset for a PS-CAR photoresist model. In embodiments, the model can be run by the PS-CAR simulation tool 604. Examples of inputs 1102 can include feature layouts, exposure kernels, EUV flare kernels, resist parameter models, and the like. In embodiments, some or all of the input parameters can be provided by the calibration unit 602. Examples of output 1104 include mask data, layout dependent variance bands, line-end shortening (LES) and process window (PW).

FIG. 12 is a schematic parameter design diagram showing an embodiment of an input dataset for a PS-CAR photoresist simulator. In embodiments, the inputs can include PS-CAR chemical inputs, exposure inputs, PEB inputs and the like. Examples of exposure inputs include secondary exposure definitions, Dill C parameters, n, k parameters in secondary (UV) exposure, PS generator gradient depth, and the like. Examples of PEB inputs include the following parameters: precursor, photosensitive, diffusible, PS generator reaction, acid quencher and neutralization. In embodiments, pre-PEB parameters can also be provided. Additional inputs to the continuum and stochastic models can be provided, as well as illumination source parameters and the like.

FIG. 13 is a schematic parameter design diagram showing an embodiment of an output data set for a PS-CAR photoresist model. In embodiments, the outputs can include continuum model profiles, stochastic model outputs, PS-CAR photoresist specific outputs associated with PS generator profiles, and secondary exposure profiles. In a further embodiment, a comparative analysis can be provided that represents a comparison of the effects of PS-CAR chemistry with another method.

FIG. 14 is a schematic parameter design diagram showing the operation of one embodiment of the primary exposure patterning optical unit 614 of the PS-CAR photoresist model tool 604. In embodiments, the primary exposure patterning optical unit 614 can include a plurality of sets of inputs, including a mask input 1402, an illumination input 1404, a stack input 1406 and a conventional continuous resist chemical input 1408. Output 1410 can include data or images representing EUV relative intensities in either 2D plane or 3D space, representing images generated by the model.

FIG. 15 is a schematic parameter design diagram showing the operation of one embodiment of the primary exposure patterning unit 616 of the PS-CAR photoresist modeling tool 604. In embodiments, the input to the module includes EUV relative intensity data 1410, which is the output of the primary exposure patterning optical unit 614. Additional inputs include a continuum resist chemical input 1502 and a scanner input 1504. The EUV unit 616 can process inputs to generate EUV exposed latent images 1506 or their dataset representations.

FIG. 16 is a schematic parameter design diagram showing the operation of one embodiment of the pre-PEB module 618 of the PS-CAR photoresist modeling tool 604. In embodiments, the input to the pre-PEB module 618 includes an EUV exposed latent image 1506, which is the output of the primary exposure patterning unit 616. Additional inputs include a continuous resist chemical input 1602 and a track input 1604. The pre-PEB module 618 can process these inputs and generate a post-PEB latent image 1606 or their data representation.

FIG. 17 is a schematic parameter design diagram showing the operation of one embodiment of the secondary optical unit 620 of the PS-CAR photoresist simulation tool 604. In embodiments, the input to the secondary optical unit 620 includes a post-pre-PEB latent image 1606 that is the output of the pre-PEB module 618. Additional inputs can include stack input 1702 and continuous resist chemical input 1704. The secondary optical unit 620 can process these inputs and generate a UV flood relative intensity image 1706 or a data representation thereof.

FIG. 18 is a schematic parameter design diagram showing the operation of one embodiment of the secondary flood exposure unit 622 of the PS-CAR photoresist simulation tool 604. In embodiments, the inputs to the secondary flood unit 622 include a latent image 1606 after pre-PEB, which is the output of the pre-PEB module 618, and a UV flood relative intensity image 1706, which is the output of the secondary optical unit 620. Additional inputs can include continuous resist chemical input 1802, UV input 1804, and the like. The secondary flood unit 622 can generate a latent image 1806 before PEB in response to these inputs.

FIG. 19 is a schematic parameter design diagram showing the operation of one embodiment of the PEB module 624 of the PS-CAR photoresist simulation tool 604. In embodiments, the input to the PEB module 624 comprises a pre-PEB latent image 1806 generated by the secondary flood unit 622. Additional inputs can include continuous resist chemical input 1902 and track input 1904. The PEB module 624 can generate a post-PEB latent image in response to these inputs.

FIG. 20 is a schematic parameter design diagram showing the operation of one embodiment of the development module 626 of the PS-CAR photoresist simulation tool 604. In an embodiment, the input to the developing module 626 includes a latent image 1906 after PEB. Additional inputs can include continuous resist chemical inputs 2002 and track inputs 2004. In response to these inputs, the development module 626 can generate the final image 2006 after development.

FIG. 21 is a schematic parameter design diagram showing the operation of one embodiment of the Metrozy module 628 of the PS-CAR photoresist simulation tool 604. In embodiments, the input to the Metrogee module 628 can include the developed final image 2006 produced by the developing module 626. Additional inputs can include Metrology inputs 2102. In response to these inputs, the Metrogee module 628 can generate a PS generator parameter output 2104 and an additional profile output 2106 containing continuity and stochastic parameters.

Those skilled in the art will appreciate the types of inputs and outputs described in the context of FIGS. 14-21 that can be processed by the various models of the PS-CAR photoresist simulation tool 604. You will realize that it is not too much. There are various other embodiments in which specific inputs or outputs are added, omitted, or modified according to model design requirements. Moreover, one of ordinary skill in the art will recognize that the model can be configured to treat the actual image as input and output, or as an alternative dataset. In certain embodiments, the dataset may represent features found in the image or the image itself.

Those skilled in the art can understand that many modifications and variations are possible in light of the above teachings. One of ordinary skill in the art will recognize various even combinations and substitutions of the various components shown in the drawings. Accordingly, the scope of the invention is intended to be limited by the appended claims, not by this detailed description.

Claims (28)

A method for calibrating a model that simulates a lithography process.
A step of calibrating initial conditions for simulation of at least one parameter of a lithography process using a radiation sensitive material, wherein the radiation sensitive material is a photosensitizing chemically amplified resist material (PS-CAR material). Including
The radiation sensitive material is
A first light wavelength activation threshold that controls the formation of acid up to the first acid concentration in the radiation sensitive material and controls the formation of photosensitizer molecules in the radiation sensitive material.
A second light wavelength activation threshold capable of exciting the photosensitizer molecule in the radiation sensitive material that produces an acid having a second acid concentration greater than the first acid concentration, the second light wavelength activity. The conversion threshold includes a second light wavelength activation threshold, which is different from the first light wavelength activation threshold.
The method further
A step of receiving at least one of the optical parameters of the radiation sensitive material, acid production and firing parameters, development rate parameters, and physical measurements of the verification experiment at the input interface.
The physical parameters of the radiation sensitive material are determined based on at least one of the received optical parameters, the acid production and firing parameters, the development rate parameters, and the physical measurements of the verification experiment. , A step of calculation using a data processor, wherein the physical parameter is the number of acid- producing agents and plurality of photosensitizers within the volume of the radiosensitive material, according to the first acid concentration. At least one of them, the step and
A step of producing an output of the physical parameters of the radiation sensitive material in the output interface, and the like.
Method. The second light that receives the first radiation exposure parameter associated with the first radiation source configured to emit radiation at the first light wavelength below the first light wavelength activation threshold and is different from the first light wavelength. It further comprises the step of receiving at the input interface a second radiation exposure parameter associated with a second radiation source configured to emit radiation at a wavelength.
The method of claim 1, wherein the calculated step comprises calculating the received first radiation exposure parameter and therefore the physical parameter. The method of claim 2, further comprising calculating the profile of the radiation sensitive material using a data processor according to a lithography process model. 2. The method of claim 2, further comprising receiving feedback at the input interface representing an error value corresponding to the comparison of the calculated physical parameter of the radiation sensitive material with the experimental verification of the physical parameter. .. The step further comprises optimizing the physical parameters and at least one of the received first radiation exposure parameters and the second radiation exposure parameters using a data processor in response to the feedback. The method according to claim 4. 4. The method of claim 4, further comprising the step of optimizing the optical parameters in response to the feedback. 4. The method of claim 4, further comprising optimizing the acid production and calcination parameters in response to the feedback. 4. The method of claim 4, further comprising the step of optimizing the development rate parameter in response to the feedback. In response to the determination that the error value is within the error threshold margin, the optimized physical parameters and the optimized first radiation exposure parameters and the optimized second radiation exposure parameters 4. The method of claim 4, further comprising the step of producing said output in an output interface, comprising at least one of them. A system for calibrating a model of a simulated lithography process.
It comprises a device with a data processor and an input interface configured to calibrate the initial conditions for simulation of at least one process parameter of a lithography process using radiation sensitive materials.
The radiation sensitive material is
The radiation-sensitive material is a photosensitizing chemically amplified resist photoresist material (PS-CAR material).
A first light wavelength activation threshold that controls the formation of acid up to the first acid concentration in the radiation sensitive material and controls the formation of photosensitizer molecules in the radiation sensitive material.
A second light wavelength activation threshold capable of exciting the photosensitizer molecule in the radiation sensitive material that produces an acid having a second acid concentration greater than the first acid concentration, the second light wavelength activity. The conversion threshold includes a second light wavelength activation threshold, which is different from the first light wavelength activation threshold.
The input interface is configured to receive data.
The data processor
A step of receiving at least one of the optical parameters of the radiation sensitive material, acid production and firing parameters, development rate parameters, and physical measurements of the verification experiment at the input interface.
The physical parameters of the radiation sensitive material are based on at least one of the optical parameters, the acid production and firing parameters, the development rate parameters, and the physical measurements received in the verification experiment. A step calculated using a data processor, the physical parameter of which is the number of acid producers and photosensitizers within the volume of the radiosensitive material, according to the first acid concentration. At least one of the steps and
It is configured to perform an operation comprising the step of generating the output of the physical parameters of the radiation sensitive material in the output interface.
system. The input interface is further different from the first radiation exposure parameters and the first light wavelength associated with the first radiation source configured to emit radiation at the first light wavelength below the first light wavelength activation threshold. It is configured to receive radiation exposure parameters associated with a second radiation source configured to emit radiation at a second light wavelength.
The calculated step comprises calculating the received first radiation exposure parameter and therefore the physical parameter.
The system according to claim 10. The operation further comprises a step of calculating the profile of the radiation sensitive material according to a lithography process model, including a step of calculating.
The system according to claim 10. The input interface is further configured to receive feedback representing error values corresponding to the comparison of the calculated physical parameters of the radiation sensitive material with the experimental verification of the physical parameters.
The system according to claim 10. The operation further comprises optimizing the physical parameters and at least one of the first radiation exposure parameters and the second radiation exposure parameters in response to the feedback.
12. The system according to claim 12. The operation further comprises a step of optimizing the optical parameters in response to the feedback.
13. The system according to claim 13. The operation further comprises optimizing the acid production and calcination parameters in response to the feedback.
13. The system according to claim 13. The operation further comprises the step of optimizing the development rate parameters in response to the feedback.
13. The system according to claim 13. With more output interface
The operation further comprises the optimized physical parameters and the optimized first radiation exposure parameters and the second radiation exposure parameters in response to the determination that the error value is within the error threshold margin. Including the step of producing an output containing at least one of them,
13. The system according to claim 13. A method for calibrating a model of a simulated lithography process.
Including the step of receiving a plurality of process parameters of a radiation sensitive material for use in the lithography process at the input interface.
The radiation-sensitive material is a photosensitizing chemically amplified resist material (PS-CAR material).
A first light wavelength activation threshold that controls the formation of acid up to the first acid concentration in the radiation sensitive material and controls the formation of photosensitizer molecules in the radiation sensitive material.
A second light wavelength activation threshold capable of exciting the photosensitizer molecule in the radiation sensitive material that produces an acid having a second acid concentration greater than the first acid concentration, the second light wavelength activity. The conversion threshold includes a second light wavelength activation threshold, which is different from the first light wavelength activation threshold.
The plurality of process parameters are physical parameters specific to PS-CAR material chemistry, a first radiation exposure parameter associated with a first radiation exposure step according to the first light activation threshold, and a second light wavelength activation threshold. 2 Includes 2nd radiation exposure parameters related to the radiation exposure step
The method further
A step of calculating the profile of the radiation sensitive material using a data processor in response to the physical parameters and the received first and second radiation exposure parameters according to a lithography process model. The profile of the radiation sensitive material comprises at least one of a number of acid generators, photosensitizers, according to the first acid concentration , within the volume of the radiation sensitive material. ,
A step of receiving feedback at the input interface that represents an error value corresponding to the comparison between the profile of the radiation sensitive material and the experimental verification of the model.
In response to the feedback, the steps of optimizing the physical parameters, the first radiation exposure parameters and the second radiation exposure parameters using the data processor.
In response to the determination that the error value is within the error threshold margin, the optimized physical parameter, the optimized first radiation exposure parameter and the second radiation exposure parameter,
Steps to generate output in the output interface, including
How to include. The calculated step further comprises at least one of a number of photodegradable quenchers, photosensitizer generators, and photosensitizers within the volume of the radiation sensitive material. Including steps to identify,
The method according to claim 1. The step of calculating the profile of the radiation sensitive material comprises identifying multiple acid-induced deprotection reactions of the photosensitizer body-producing agent for conversion to the photosensitizer.
The method according to claim 20. The step of calculating the profile of the radiation sensitive material is a plurality of photons of the first light wavelength in the first radiation exposure step or the second light wavelength in the second radiation exposure step, which are absorbed by the volume of the radiation sensitive material. Including steps to identify
The method according to claim 20. The step of calculating the profile of the radiation sensitive material is by the first radiation exposure step or by the photosensitizer activation by the second radiation exposure step and the subsequent acid generative decomposition by the excited photosensitizer. Including the step of identifying the number of acid-producing agents converted to acid,
22. The method of claim 22. The step of calculating the profile of the radiation sensitive material comprises identifying the number of photodegradable quenchers decomposed by the first radiation exposure step or the second radiation exposure step.
The method according to claim 20. The step of calculating the profile of the radiation sensitive material comprises identifying a number of acids and quencher neutralization reactions within the volume of the radiation sensitive material.
The method according to claim 20. The step of calculating the profile of the radiation sensitive material comprises identifying the number of acid-induced deprotection reactions of the protecting polymer.
The method according to claim 20. 20. The method of claim 20, wherein the step of calculating the profile of the radiosensitive material comprises calculating the development of the volume of the radiosensitive material. The step of calculating the profile of the radiosensitive material is the step of creating a two-dimensional or three-dimensional image of the physical parameters of the radiosensitive material formed by developing the volume of the radiosensitive material with the data processor. include,
27. The method of claim 27.

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